An assessment of nudging techniques for regional climate modeling: Multi-year NCEP-NCAR reanalysis driven simulations

The Environmental Protection Agency (EPA) is in the process of developing dynamically downscaling capabilities in the response to the growing needs of regional climate projections for impact assessment. Having the expertise in-house allows the EPA to better adapt to a particular impact and provide the impact community an assessment of the model uncertainties. This study focuses on four dimensional data assimilation for dynamical downscaling using the Weather Research and Forecasting (WRF) model. This study will explore the sensitivity of analysis nudging versus spectral nudging for multi-year simulations driven by the NCEP-NCAR reanalysis data. Using the coarser reanalysis data provides us an idealized way how to incorporate such nudging techniques to climate change projections driven by GCMs. The biases of each sensitivity simulation compared to a base simulation with no nudging will illustrate the sensitivity of the nudging to the mean and variance. Additionally, physics options are known to have a huge impact on regional climate change simulations. Specifically, we will address the choice of the land surface model in WRF and its relative impact on the bias with respect to nudging.